Solution

The project stages included building a specific CNN structure; preparing training and testing datasets; training and testing the CNN, and evaluating accuracy.

ScienceSoft’s team of senior С++ engineers created a CNN structure with the following layers:

5 convolutional layers

1 ReLU activation layer

1 pooling layer

1 fully connected layer

The MRI analysis process included:

Segmentation of 3 planes - XY, XZ and YZ

Application of 3 post-processing filters to remove noise and other artifacts

Merging of 3 output files into one

Application of the final post-processing filter to the merged file

To evaluate CNN performance, the team compared acquired results with the ground truth. The ground truth was taken from BRATS imaging datasets, which have been segmented and annotated manually by one to four raters as well as approved by neuro-radiologists. The maximum network accuracy achieved is 87%.